OpenRaiser/Intern-Atlas huggingface dataset:
Towards Making High Dimensional Distance Metric Learning Practical
Venue: arXiv cs.LG 2015
Year: 2015

In this work, we study distance metric learning (DML) for high dimensional data. A typical approach for DML with high dimensional data is to perform the dimensionality reduction first before learning the distance metric. The main shortcoming of this approach is that it may result in a suboptimal solution due to the subspace removed by the dimensionality reduction method. In this work, we present a dual random projection frame for DML with high dimensional data that explicitly addresses the limitation of dimensionality reduction for DML. The key idea is to first project all the data points into a low dimensional space by random projection, and compute the dual variables using the projected vectors. It then reconstructs the distance metric in the original space using the estimated dual variables. The proposed method, on one hand, enjoys the light computation of random projection, and on the other hand, alleviates the limitation of most dimensionality reduction methods. We verify both empirically and theoretically the effectiveness of the proposed algorithm for high dimensional DML.
Kannada named entity recognition and classification (nerc) based on multinomial naïve bayes (mnb) classifier
Venue: arXiv cs.CL 2015
Year: 2015

Named Entity Recognition and Classification (NERC) is a process of identification of proper nouns in the text and classification of those nouns into certain predefined categories like person name, location, organization, date, and time etc. NERC in Kannada is an essential and challenging task. The aim of this work is to develop a novel model for NERC, based on Multinomial Naïve Bayes (MNB) Classifier. The Methodology adopted in this paper is based on feature extraction of training corpus, by using term frequency, inverse document frequency and fitting them to a tf-idf-vectorizer. The paper discusses the various issues in developing the proposed model. The details of implementation and performance evaluation are discussed. The experiments are conducted on a training corpus of size 95,170 tokens and test corpus of 5,000 tokens. It is observed that the model works with Precision, Recall and F1-measure of 83%, 79% and 81% respectively.
Resilient Big Data Monetization
Venue: arXiv cs.NI 2015
Year: 2015

Resilient Big Data monetization is devised as k-dominance and m-connectivity problems, such that common-interests are connected by k-ways to measurement tools, which are tied within each other in m-ways. Consequently, a greedy approximation algorithm Plutus (i.e resembling Greek god of wealth) is proposed, which isolates measurement tools to ac-quire domination over common-interests, establishes synergy from common-interests to measurement tools and then acquires divergence and sustains it within measurement tools
Assisted Coverage Closure
Venue: arXiv cs.SE 2015
Year: 2015

The malfunction of safety-critical systems may cause damage to people and the environment. Software within those systems is rigorously designed and verified according to domain specific guidance, such as ISO26262 for automotive safety. This paper describes academic and industrial co-operation in tool development to support one of the most stringent of the requirements --- achieving full code coverage in requirements-driven testing. We present a verification workflow supported by a tool that integrates the coverage measurement tool RapiCover with the test-vector generator FShell. The tool assists closing the coverage gap by providing the engineer with test vectors that help in debugging coverage-related code quality issues and creating new test cases, as well as justifying the presence of unreachable parts of the code in order to finally achieve full effective coverage according to the required criteria. To illustrate the practical utility of the tool, we report about an application of the tool to a case study from automotive industry.
Cost Efficient Design of Reversible Adder Circuits for Low Power Applications
Venue: arXiv cs.AR 2015
Year: 2015

A large amount of research is currently going on in the field of reversible logic, which have low heat dissipation, low power consumption, which is the main factor to apply reversible in digital VLSI circuit design. This paper introduces reversible gate named as Inventive0 gate. The novel gate is synthesis the efficient adder modules with minimum garbage output and gate count. The Inventive0 gate capable of implementing a 4-bit ripple carry adder and carry skip adders.It is presented that Inventive0 gate is much more efficient and optimized approach as compared to their existing design, in terms of gate count, garbage outputs and constant inputs. In addition, some popular available reversible gates are implemented in the MOS transistor design the implementation kept in mind for minimum MOS transistor count and are completely reversible in behavior more precise forward and backward computation. Lesser architectural complexity show that the novel designs are compact, fast as well as low power.
Driver Friendly Headlight Controller for Driving in Developing Countries
Venue: arXiv cs.SY 2015
Year: 2015

In developing countries, night driving is extremely unsafe mainly due to; 1). Poorly followed traffic rules and 2) bad road conditions. The number of accidents is increasing at a frightening pace, necessitating the development of a low cost automatic headlight control system to ensure safety. In most accident cases, fatal collisions take place due to glare generated by excessive headlight intensity (high beam) of the oncoming vehicle. In this paper, a user friendly controller for headlight intensity control for driving on highway at night has been proposed. Aim is to design simple and affordable system that can alleviate effect of blind spot due to high glare on the vehicle windscreen. Controller is based on Fuzzy inference system (FIS) and used incoming light intensity as criteria. Also, relative distance and speed is derived using incoming intensity of the oncoming vehicles. The system is designed considering human tolerance levels of light intensity as the boundary values. The system controls headlight beam voltage such that; a) intensity is maintained in human visual comfort zone and b) blind spot is avoided. The super user feature incorporated in the intensity controller offers personalized preferences to the driver. Due to the use of the single parameter (intensity) for control, system can be implemented using simplified hardware.
ÆtherFlow: Principled Wireless Support in SDN
Venue: arXiv cs.NI 2015
Year: 2015

Software Defined Networking (SDN) drastically changes the meaning and process of designing, building, testing, and operating networks. The current support for wireless net- working in SDN technologies has lagged behind its development and deployment for wired networks. The purpose of this work is to bring principled support for wireless access networks so that they can receive the same level of programmability as wireline interfaces. Specifically we aim to integrate wireless protocols into the general SDN framework by proposing a new set of abstractions in wireless devices and the interfaces to manipulate them. We validate our approach by implementing our design as an extension of an existing OpenFlow data plane and deploying it in an IEEE 802.11 access point. We demonstrate the viability of software-defined wireless access networks by developing and testing a wireless handoff application. The results of the exper- iment show that our framework is capable of providing new capabilities in an efficient manner.
Group Membership Prediction
Venue: arXiv cs.CV 2015
Year: 2015

The group membership prediction (GMP) problem involves predicting whether or not a collection of instances share a certain semantic property. For instance, in kinship verification given a collection of images, the goal is to predict whether or not they share a {\it familial} relationship. In this context we propose a novel probability model and introduce latent {\em view-specific} and {\em view-shared} random variables to jointly account for the view-specific appearance and cross-view similarities among data instances. Our model posits that data from each view is independent conditioned on the shared variables. This postulate leads to a parametric probability model that decomposes group membership likelihood into a tensor product of data-independent parameters and data-dependent factors. We propose learning the data-independent parameters in a discriminative way with bilinear classifiers, and test our prediction algorithm on challenging visual recognition tasks such as multi-camera person re-identification and kinship verification. On most benchmark datasets, our method can significantly outperform the current state-of-the-art.
Coverage-Driven Verification - An approach to verify code for robots that directly interact with humans
Venue: arXiv cs.RO 2015
Year: 2015

Collaborative robots could transform several industries, such as manufacturing and healthcare, but they present a significant challenge to verification. The complex nature of their working environment necessitates testing in realistic detail under a broad range of circumstances. We propose the use of Coverage-Driven Verification (CDV) to meet this challenge. By automating the simulation-based testing process as far as possible, CDV provides an efficient route to coverage closure. We discuss the need, practical considerations, and potential benefits of transferring this approach from microelectronic design verification to the field of human-robot interaction. We demonstrate the validity and feasibility of the proposed approach by constructing a custom CDV testbench and applying it to the verification of an object handover task.
Maximum Matching in General Graphs Without Explicit Consideration of Blossoms Revisited
Venue: arXiv cs.DS 2015
Year: 2015

We reduce the problem of finding an augmenting path in a general graph to a reachability problem in a directed bipartite graph. A slight modification of depth-first search leads to an algorithm for finding such paths. Although this setting is equivalent to the traditional terminology of blossoms due to Edmonds, there are some advantages. Mainly, this point of view enables the description of algorithms for the solution of matching problems without explicit analysis of blossoms, nested blossoms, and so on. Exemplary, we describe an efficient realization of the Hopcroft-Karp approach for the computation of a maximum cardinality matching in general graphs and a variant of Edmonds' primal-dual algorithm for the maximum weighted matching problem.
Background-tracking Acoustic Features for Genre Identification of Broadcast Shows
Venue: arXiv cs.SD 2015
Year: 2015

This paper presents a novel method for extracting acoustic features that characterise the background environment in audio recordings. These features are based on the output of an alignment that fits multiple parallel background--based Constrained Maximum Likelihood Linear Regression transformations asynchronously to the input audio signal. With this setup, the resulting features can track changes in the audio background like appearance and disappearance of music, applause or laughter, independently of the speakers in the foreground of the audio. The ability to provide this type of acoustic description in audiovisual data has many potential applications, including automatic classification of broadcast archives or improving automatic transcription and subtitling. In this paper, the performance of these features in a genre identification task in a set of 332 BBC shows is explored. The proposed background--tracking features outperform short--term Perceptual Linear Prediction features in this task using Gaussian Mixture Model classifiers (62% vs 72% accuracy). The use of more complex classifiers, Hidden Markov Models and Support Vector Machines, increases the performance of the system with the novel background--tracking features to 79% and 81% in accuracy respectively.
Overcomplete Dictionary Learning with Jacobi Atom Updates
Venue: arXiv cs.CV 2015
Year: 2015

Dictionary learning for sparse representations is traditionally approached with sequential atom updates, in which an optimized atom is used immediately for the optimization of the next atoms. We propose instead a Jacobi version, in which groups of atoms are updated independently, in parallel. Extensive numerical evidence for sparse image representation shows that the parallel algorithms, especially when all atoms are updated simultaneously, give better dictionaries than their sequential counterparts.
Generalized Model of VSC-based Energy Storage Systems for Transient Stability Analysis
Venue: arXiv cs.SY 2015
Year: 2015

This paper presents a generalized energy storage system model for voltage and angle stability analysis. The proposed solution allows modeling most common energy storage technologies through a given set of linear differential algebraic equations (DAEs). In particular, the paper considers, but is not limited to, compressed air, superconducting magnetic, electrochemical capacitor and battery energy storage devices. While able to cope with a variety of different technologies, the proposed generalized model proves to be accurate for angle and voltage stability analysis, as it includes a balanced, fundamental-frequency model of the voltage source converter (VSC) and the dynamics of the dc link. Regulators with inclusion of hard limits are also taken into account. The transient behavior of the generalized model is compared with detailed fundamental-frequency balanced models as well as commonly-used simplified models of energy storage devices. A comprehensive case study based on the WSCC 9-bus test system is presented and discussed.
Computing stable outcomes in symmetric additively-separable hedonic games
Venue: arXiv cs.GT 2015
Year: 2015

We study the computational complexity of finding stable outcomes in hedonic games, which are a class of coalition formation games. We restrict our attention to symmetric additively-separable hedonic games, which are a nontrivial subclass of such games that are guaranteed to possess stable outcomes. These games are specified by an undirected edge- weighted graph: nodes are players, an outcome of the game is a partition of the nodes into coalitions, and the utility of a node is the sum of incident edge weights in the same coalition. We consider several stability requirements defined in the literature. These are based on restricting feasible player deviations, for example, by giving existing coalition members veto power. We extend these restrictions by considering more general forms of preference aggregation for coalition members. In particular, we consider voting schemes to decide if coalition members will allow a player to enter or leave their coalition. For all of the stability requirements we consider, the existence of a stable outcome is guaranteed by a potential function argument, and local improvements will converge to a stable outcome. We provide an almost complete characterization of these games in terms of the tractability of computing such stable outcomes. Our findings comprise positive results in the form of polynomial-time algorithms, and negative (PLS-completeness) results. The negative results extend to more general hedonic games.
Elements of Validation of Artificial Lighting through the Software CODYRUN: Application to a Test Case of the International Commission on Illumination (CIE)
Venue: arXiv cs.GR 2015
Year: 2015

CODYRUN is a software for computational aeraulic and thermal simulation in buildings developed by the Laboratory of Building Physics and Systems (L.P.B.S). Numerical simulation codes of artificial lighting have been introduced to extend the tool capacity. These calculation codes are able to predict the amount of light received by any point of a given working plane and from one or more sources installed on the ceiling of the room. The model used for these calculations is original and semi-detailed (simplified). The test case references of the task-3 TC-33 International Commission on Illumination (CIE) were applied to the software to ensure reliability to properly handle this photometric aspect. This allowed having a precise idea about the reliability of the results of numerical simulations.
Computing the Rectilinear Center of Uncertain Points in the Plane
Venue: arXiv cs.CG 2015
Year: 2015

In this paper, we consider the rectilinear one-center problem on uncertain points in the plane. In this problem, we are given a set $P$ of $n$ (weighted) uncertain points in the plane and each uncertain point has $m$ possible locations each associated with a probability for the point appearing at that location. The goal is to find a point $q^*$ in the plane which minimizes the maximum expected rectilinear distance from $q^*$ to all uncertain points of $P$, and $q^*$ is called a rectilinear center. We present an algorithm that solves the problem in $O(mn)$ time. Since the input size of the problem is $Θ(mn)$, our algorithm is optimal.
A Study Investigating Typical Concepts and Guidelines for Ontology Building
Venue: arXiv cs.AI 2015
Year: 2015

In semantic technologies, the shared common understanding of the structure of information among artifacts (people or software agents) can be realized by building an ontology. To do this, it is imperative for an ontology builder to answer several questions: a) what are the main components of an ontology? b) How an ontology look likes and how it works? c) Verify if it is required to consider reusing existing ontologies or not? c) What is the complexity of the ontology to be developed? d) What are the principles of ontology design and development? e) How to evaluate an ontology? This paper answers all the key questions above. The aim of this paper is to present a set of guiding principles to help ontology developers and also inexperienced users to answer such questions.
Composing vibrotactile music: A multisensory experience with the Emoti-chair
Venue: arXiv cs.HC 2015
Year: 2015

The Emoti-Chair is a novel technology to enhance entertainment through vibrotactile stimulation. We assessed the experience of this technology in two workshops. In the first workshop, deaf film-makers experimented with creating vibetracks for a movie clip using a professional movie editing software. In the second workshop, trained opera singers sang and felt their voice through the Emoti-Chair. Participants in both workshops generally found the overall experience to be exciting and they were motivated to use the Chair for upcoming projects.
A heuristic approach for designing cyclic group codes
Venue: arXiv cs.IT 2015
Year: 2015

In this paper we propose a heuristic technique for distributing points on the surface of a unit n-dimensional Euclidean sphere, generated as the orbit of a finite cyclic subgroup of orthogonal matrices, the so called cyclic group codes. Massive numerical experiments were done and many new cyclic group codes have been obtained in several dimensions at various rate. The obtained results assure that the heuristic approach have performance comparable to a brute-force search technique with the advantage of having low complexity, allowing for designing codes with a large number of points in higher dimensions.
Challenges and Considerations for Utilizing Burst Buffers in High-Performance Computing
Venue: arXiv cs.DC 2015
Year: 2015

As high-performance computing (HPC) moves into the exascale era, computer scientists and engineers must find innovative ways of transferring and processing unprecedented amounts of data. As the scale and complexity of the applications running on these machines increases, the cost of their interactions and data exchanges (in terms of latency, energy, runtime, etc.) can increase exponentially. In order to address I/O coordination and communication issues, computing vendors are developing an intermediate layer between compute nodes and the parallel file system composed of different types of memory (NVRAM, DRAM, SSD). These large scale memory appliances are being called 'burst buffers.' In this paper, we envision advanced memory at various levels of HPC hardware and derive potential use cases for how to take advantage of it. We then present the challenges and issues that arise when utilizing burst buffers in next-generation supercomputers and map the challenges to the use cases. Lastly, we discuss the emerging state-of-the-art burst buffer solutions that are expected to become available by the end of the year in new HPC systems and which use cases these implementations may satisfy.
FPTAS for Hardcore and Ising Models on Hypergraphs
Venue: arXiv cs.DS 2015
Year: 2015

Hardcore and Ising models are two most important families of two state spin systems in statistic physics. Partition function of spin systems is the center concept in statistic physics which connects microscopic particles and their interactions with their macroscopic and statistical properties of materials such as energy, entropy, ferromagnetism, etc. If each local interaction of the system involves only two particles, the system can be described by a graph. In this case, fully polynomial-time approximation scheme (FPTAS) for computing the partition function of both hardcore and anti-ferromagnetic Ising model was designed up to the uniqueness condition of the system. These result are the best possible since approximately computing the partition function beyond this threshold is NP-hard. In this paper, we generalize these results to general physics systems, where each local interaction may involves multiple particles. Such systems are described by hypergraphs. For hardcore model, we also provide FPTAS up to the uniqueness condition, and for anti-ferromagnetic Ising model, we obtain FPTAS where a slightly stronger condition holds.
Finding Two Edge-Disjoint Paths with Length Constraints
Venue: arXiv cs.DS 2015
Year: 2015

We consider the problem of finding, for two pairs $(s_1,t_1)$ and $(s_2,t_2)$ of vertices in an undirected graphs, an $(s_1,t_1)$-path $P_1$ and an $(s_2,t_2)$-path $P_2$ such that $P_1$ and $P_2$ share no edges and the length of each $P_i$ satisfies $L_i$, where $L_i \in \{ \le k_i, \; = k_i, \; \ge k_i, \; \le \infty\}$. We regard $k_1$ and $k_2$ as parameters and investigate the parameterized complexity of the above problem when at least one of $P_1$ and $P_2$ has a length constraint (note that $L_i = "\le \infty"$ indicates that $P_i$ has no length constraint). For the nine different cases of $(L_1, L_2)$, we obtain FPT algorithms for seven of them. Our algorithms uses random partition backed by some structural results. On the other hand, we prove that the problem admits no polynomial kernel for all nine cases unless $NP \subseteq coNP/poly$.
LIRA: A Location Independent Routing Layer based on Source-Provided Ephemeral Names
Venue: arXiv cs.NI 2015
Year: 2015

We identify the obstacles hindering the deployment of Information Centric Networking (ICN) and the shift from the current IP architecture. In particular, we argue that scalability of name resolution and the lack of control of content access from content providers are two important barriers that keep ICN away from deployment. We design solutions to incentivise ICN deployment and present a new network architecture that incorporates an extra layer in the protocol stack (the Location Independent Routing Layer, LIRA) to integrate location-independent content delivery. According to our design, content names need not (and should not) be permanent, but rather should be ephemeral. Resolution of non-permanent names requires the involvement of content providers, enabling desirable features such as request logging and cache purging, while avoiding the need for the deployment of a new name resolution infrastructure. Our results show that with half of the network's nodes operating under the LIRA framework, we can get the full gain of the ICN mode of operation.